This talk is for people with large and varied data who are interested in novel applications of data analytics, machine learning, and visualization to influence stakeholders and put the power of data to work for their businesses. We’ll walk through three case studies where we have delivered insights and/or products that blend data and experiences from physical and online commerce:

In the process we’ll discuss the challenges, tools, and techniques we employed along the way. We’ll also cover how the development of rapid prototype user interfaces have proven a powerful tool for conveying insights to and gaining support from business stakeholders. Some of the technologies that will be discussed include: R, Python, Ruby, d3.js, and Node.js.

Businesses are inundated with options of vendors who provide analytical products. We're told in no uncertain terms that without real-time analytical capabilities we are being out-strategized, out-advertised and out-personalized with every passing second. "Real-time real talk" is a critical survey of real-time systems and their application in the areas of retail and marketing. We'll cut through the hype and get to the heart of what it means to be real-time, and explore some of the real-time systems being built today in the Nordstrom Data Lab.

This beginner workshop will cover how to consume Twitters' API and cover the basics of API consumption such as http requests, oauth, and what you can do with the data once you extract it. Hope to see you there!

Predicting the future is hard and it requires a lot of assumptions, also known as beliefs, also known as faith. In “Assumptions: Check yo self, before you wreck yo self” we explore the consequences of beliefs when constructing predictive models. We’ll walk through the process of developing a demand forecast for Evo, a Seattle-based outdoor recreation retailer, and discuss how assumptions influence the behavior of your application and ultimately the decisions you make.

Twitter makes money by selling ads, but they’ve got an insidious infestation eroding their advertising credibility: bots. These bots are automatons living in the Twittersphere, ranging wildly in capability. In Bot or Not I’ll discuss how to identify bots with a classification algorithm created in scikit-learn and provide some tips on how to account for them when analyzing social media experiments.